Month: October 2015

I originally intended on including and briefly discussing these values in my “Ethnic/Race Differences in Aptitude” paper since therein I touched upon differences in Asian American subgroup performance (e.g., Table 15 and Table 17). Alas, I ran out of both space and my reviewers’ patience. Since the general topic continues to arise, I thought I might mention them, though. The 1996 and 2000 National Postsecondary Student Aid Studies (NPSAS 1996/2000), which were representative of the university populations at the respective times, contained both an “Asian origin” variable and a composite SAT score one, thus allowing for some investigation of subgroup variability. In expressing the differences, I used citizen/U.S. born White values as a reference for the SAT scores. Standardized differences were computed using the total group standard deviations, since population specific ones were unavailable. NA means that the sample sizes did not meet NCESDataLab’s cutoff for reportability. And negative values mean that the groups in question performed better than U.S. born/citizen Whites. As the confidence intervals — not shown below — were large for all of the Asian subgroups, results should be interpreted with caution. It’s notable that there were large U.S. born/non-U.S. born effects for both East and South Asians. The scores were for college students, so this might represent a foreign student effect (as opposed to a generation 1/generation 2+ immigrant one).

NPSAS 1996 and 2000

1996

2000

Nationality

non-Citizen

Citizen

All

Nationality

Not US Born

US BORN

All

Chinese

0.01

-0.66

-0.44

Chinese

-0.28

-0.64

-0.46

Korean

-0.38

-0.63

-0.54

Korean

-0.12

-0.82

-0.37

Japanese

NA

NA

-0.79

Japanese

NA

-0.20

-0.06

Filipino

NA

-0.17

-0.13

Filipino

NA

0.03

0.12

Vietnamese

0.86

-0.18

0.31

Vietnamese

0.61

NA

0.39

Asian Indian

0.47

-0.96

-0.43

Asian Indian

0.22

-0.88

-0.24

Asian/PI (total)

0.29

-0.37

-0.19

Asian/PI (total)

0.10

-0.41

-0.12

White

0.08

Reference

0.00

White

-0.03

Reference

0.03

Black

0.84

0.87

0.87

Black

0.74

1.00

0.96

Used the total group standard deviation
Source: //nces.ed.gov/surveys/npsas/

Attempts to assess population aptitude from elite achievement go back to at least Galton. In Hereditary Genius, Galton used an estimate of the number of eminent persons produced by various ethnic and racial groups to quantify the differences between the means of these groups. Since his time, variants and refinements of this genre of analysis have become frequent. In “The Racial Origin of Successful Americans (1914)” Frederick Woods attempted to estimate ethnic achievement by counting and classifying the number of ethnic surnames in Marquis’ “Who’s Who” list. Lauren Ashe (1915) improved on the strategy by determining the representation of ethnic names in “Who’s Who” relative to that found in various U.S. city populations. In the 1960s, Nathaniel Weyl developed a variant of the “Who’s Who” surname method, one which relied on rare surnames, and in the 1980s he applied the method to National Merit Scholarship (NMS) lists (1), which record those high school seniors who obtained the top scores on College Board’s Preliminary SAT/National Merit Scholarship Qualifying Test (PSAT/NMSQT).

Chanda Chisala, a visiting Fellow at Stanford University, has developed what he considers to be a devastating argument against Jensenism (racial-IQ-hereditarianism). He develops this in his 2014 blog post, “Killing Jensen — part I“. Pithily put, the reasoning runs: